Realization of processing blocks of CNN based CASA system on CPU and FPGA

O. Levent Şavkay, Evren Cesur, Nerhun Yildiz, Müştak E. Yalcin, Vedat Tavşanoǧlu

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

3 Atıf (Scopus)

Özet

In this paper, hardware optimization of the preprocessing and software implementation of the processing blocks of a computer-aided semen analysis (CASA) system are proposed, which is also implemented on an FPGA and ARM device as a working prototype. The software implementation of the track initialization, track maintenance, data validation and classification blocks of the processing part are implemented on a Zynq7000 ARM Cortex-A9 processor. In the preprocessing part, a real-time cellular neural network (CNN) emulator (RTCNNP-v2) is used for the realization of the image processing algorithms, whose regular, flexible and reconfigurable infrastructure simplifies the prototyping process. The CASA system introduced in this paper is capable of processing full-HD 1080p@60 (1080 × 1920) video images in real-time.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığı2014 IEEE International Symposium on Circuits and Systems, ISCAS 2014
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
Sayfalar2081-2084
Sayfa sayısı4
ISBN (Basılı)9781479934324
DOI'lar
Yayın durumuYayınlandı - 2014
Etkinlik2014 IEEE International Symposium on Circuits and Systems, ISCAS 2014 - Melbourne, VIC, Australia
Süre: 1 Haz 20145 Haz 2014

Yayın serisi

AdıProceedings - IEEE International Symposium on Circuits and Systems
ISSN (Basılı)0271-4310

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???event.eventtypes.event.conference???2014 IEEE International Symposium on Circuits and Systems, ISCAS 2014
Ülke/BölgeAustralia
ŞehirMelbourne, VIC
Periyot1/06/145/06/14

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